Ingest corporate Data Exhaust for better Employee Engagement

Definition - Data exhaust refers to the data generated as trails or information byproducts resulting from the digital/online activities. These consist of storable choices, actions and preferences such as log files, cookies, temporary files and even information that is generated for every process or transaction done digitally.

The term 'data exhaust' has been around for a decade and its recognition came in timely along-side big data. It has always been the oracular digital sub-conscious working behind the curtains, tweaking the landscape aptly based on the user's digital footprint. In true senses, it is the modern day data science equivalent of the old adage "one man's trash is another man's treasure".

Data exhaust has gotten its due limelight in the commercial space and has been put into good use by the tech giants to build efficacious business models around it. The story so far has been outward looking (customer facing), rightly so, for all the economic/business reasons. However, with the increasing focus towards improving employee engagement internally, it's time to exploit data exhaust's potential inwards. The employees spend considerable amount of time using office network via desktop/laptop/handheld device, thus generating goodly amount of data exhaust to tap into. This inward looking endeavor can be equally benefiting for the companies, as the prime asset in knowledge industry is human workforce. Here are some of the areas where it can provide useful insights.

1. Provide assistance / Up-skill: For frequently searched areas build a pattern result set and present for reference. In case of regular assistance being sought on certain topic, propose corresponding trainings to up-skill.

2. Understand areas of strength: Lookout for the areas where contribution is recurring and which all forums/blogs etc. are regularly visited.

3. Understand usage of company's internal tools/portals: Gather useful insight about the frequency, usage of internal tools etc. and based on that better align them to cater to the needs.

4. Personalized rewards & recognition: Understand personal preferences better and thereby reward appropriately.

5. Highlight non-productive areas where time is being spent

6. And many more based on the industry and how efficiently the data is ingested

Looking at the potential of data exhaust there is no doubt about the transformation it can bring about. However, to bring it into that shape there are a number of factors to take into account.

• It's BIG: The amount of data collected is colossal, though the storage cost is on the decline yet the resources required to store and process data this size are substantial.

• Brace for a lot of data janitorial work: Having a bowl full of data is no fun until there is realization about how to make sense out of it all. One of the hardest pieces of working with exhaust data is getting a single coherent view around it. Cleaning up and unifying that data can be a challenge.

• Cautiously draw the line: If the analysis of data collected via exhaust channel is not presented discretely then there is a high risk of losing trust, as the end user may not be in acceptance of this level of surveillance.

Thinking of it, data exhaust is the evil twin of big data but can provide vital insights which may not be so evident in plain view. When there are avenues available today to tap this excess data then why let it drain away, instead it should be utilized to appease both outward and inward stakeholders.